摘要
稀疏分解算法是信号稀疏分解领域的一个重点问题,关系到稀疏分解在实际中的应用。在分析平滑l0算法的基础上,提出了基于拟牛顿方向的平滑l0算法。该算法在求解l0范数的近似函数最优解时,取代平滑l0算法中的最速上升方法,以拟牛顿方向作为迭代搜索方向。仿真结果表明,利用基于拟牛顿方向的平滑l0算法对信号进行稀疏分解,得到的稀疏分解系数精确度更高,与真实系数之间的误差更小,信噪比更大,抗噪声能力更强。
The sparse decomposition algorithm is an important problem in the signal sparse decomposition, and is related to the factual application. The smoothed l_0norm approximation algorithm based on the Quasi-Newton direction is proposed, and on the algorithm the Quasi-Newton direction is used instead of the steepest ascent direction when maximizing the approximation function of l_0 norm. The experimental results show that the proposed algorithm is efficient to the signal sparse decomposition and has the better ability to anti-noise-jamming, the decomposition coefficient is more accurate and the signal-to-noise is bigger with the algorithm.
出处
《计算机工程与应用》
CSCD
2013年第22期215-218,共4页
Computer Engineering and Applications
基金
国家自然科学基金(No.61003148)
关键词
平滑l0算法
拟牛顿方向
最速上升方向
稀疏分解
smoothed l_0 approximation algorithm
Quasi-Newton direction
steepest ascent direction
sparse decomposition
